1. CS 425/625 Software Engineering System Models
Based on Chapter 7 of the textbook [Somm00] Ian Sommerville,
Software Engineering, 6th Ed., Addison-Wesley, 2000 and on
Ch7 PowerPoint presentation available at the book’s web-site:
September 29, 2003

2. Outline System Models Contextual Models Behavioral Models Data Models
Object Models

3. Introduction.
System models are used to specify the system to be built in a more detailed way
Typically, system models are graphical descriptions of the system, its services and its constraints
Various perspectives for system modeling:
Context
Behavior
Structure

4. .Introduction
The production of system models is usually guided by methods, e.g., SSA (Structured Systems Analysis), SADT (Structured Analysis and Design Technique), OMT (Object Modeling Technique), etc.
In practice, various models, not bound to methods, could be combined to describe the system and its requirements
Main types of system models:
Data Processing Models
Composition Models
Architectural Models
Classification Models
Stimulus-Response Models

5. Context Models… Contextual models show the system and its environment
Ideally, the boundaries between the system and its environment are identified clearly
Dependencies between the computer-based system and systems from the environment are highlighted

6. .Context Models.. Various models can be used for context modeling:
Very simple, high level architectural models show the system and its connections with environmental components
High level process models indicate main process activities
High-level data-flow diagrams depict data transformations and data transfers

7. ..Context Models.
Example of architectural model for system context specification: an ATM system and its environment [Fig. 7.1, Somm00]

8. …Context Models
Example of process model for system context specification: an equipment procurement system [Fig. 7.2, Somm00]

9. Behavioral Models…….
Behavioral models specify the overall behavior of the system:
Data-flow models (or data-flow diagrams, DFD) are suitable for data-driven systems
State machine models (or stimulus-response models) are appropriate for event-driven systems

10. .Behavioral Models…... Data-flow models show the system in terms of:
Data stores
[graphical representation: rectangles]
Data transformations (data processing operations)
[graphical representation: rounded rectangles]
Data movements (data transfers)
[graphical representation: directed lines]

11. ..Behavioral Models…..
State machine models describe system behavior using two main modeling elements:
States
[represented using rounded rectangles]
Transitions
[shown as directed links between states]

12. …Behavioral Models....
A DFD example: an order processing system [Fig. 7.3, Somm00]

13. ….Behavioral Models…
State machine diagrams depict the behavior of the system in terms of responses to events
Real-time systems are essentially event-driven systems
The system is assumed to be in one of its possible states at any given moment of time. A transition to another state is triggered by the occurrence of an event
David Harel’s statecharts are included in the UML (Unified Modeling Language); DFDs are not part of UML

14. …..Behavioral Models..
Example of state machine diagram: A microwave oven controller [Fig. 7.5, Somm00]

15. …...Behavioral Models. The statecharts notation used in UML allows:
Specification of composite states (states that have sub-states), thus supporting model decomposition
Description of actions performed while in a state:
Entry actions
State actions (activities)
Exit actions
Description of transitions:
Events that trigger the transition
Conditions under which transitions occur
Actions on transitions, if any

16. …....Behavioral Models
Example of composite state: microwave oven [Fig. 7.7, Somm00]

17. Semantic Data Models…
Data models describe the logical structure of data processed by the system
The Entity-Relationship-Attribute model, ERA (also known as Entity-Relationship model, ER) shows:
Entities in the system
Relationships between entities
Attributes of entities and relationships
Cardinality constraints (e.g., “one” or “many”)

18. .Semantic Data Models..
Data dictionaries are repositories of information pertaining to the elements of the system models. They are useful to manage the namespace of the system models as well as to supply a cross-reference tool for analysis, design, implementation, and evolution.

19. ..Semantic Data Models.
An ERA example: a software design description [Fig. 7.8, Somm00]

20. …Semantic Data Models
Data dictionary: examples of data entries [Fig. 7.9, Somm00]

21. Object Models……..
Objected-oriented modeling is centered around the concepts of object and class
An object is an entity described in terms of attributes (data) and operations (functionality)
A class is a template for objects that have similar features (attributes and operations).
More exactly, the objects that belong to the same class have the same structure and behavior, e.g., davidsAlarmClock is an object (instantiation) of the class AlarmClock

22. .Object Models…….
The distinguishing principles of object-oriented (OO) technology are:
Encapsulation
Inheritance
Polymorphism

23. ..Object Models……
Objects provide more natural ways to model real-life entities
Both structure (class diagrams) and behavior (e.g., interaction diagrams and state diagrams) can be described
A class diagram shows:
Classes
Relationships between classes
Constraints
Annotations

24. …Object Models….. The value of OO comes from: Greater modeling power
Increased reusability and extensibility
Improved control of complexity

25. ….Object Models….
Example of class hierarchy: a library system [Fig. 7.10, Somm00]

26. …..Object Models…
Another example of class hierarchy: Library users [Fig. 7.11, Somm00]

27. ……Object Models..
Example of multiple inheritance [Fig. 7.12, Somm00]

28. …….Object Models.
Example of class structure with aggregation [Fig. 7.13, Somm00]

29. ……..Object Models
Example of sequence diagram [Fig. 7.14, Somm00]